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Against Method: Table 1-Cui Bono?

Bernhard Rupp1

  • 1k.-k.Hofkristallamt, San Diego, CA 92084, USA; Division of Genetic Epidemiology, Medical University Innsbruck, Schöpfstraße 41, Innsbruck, Tyrol 6020, Austria.

Structure (London, England : 1993)
|June 5, 2018
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Summary
This summary is machine-generated.

The traditional "Table 1" in biomolecular crystallography reports is outdated and insufficient. A new approach focusing on direct data quality metrics and reciprocal space analysis should replace it for better experimental evaluation.

Keywords:
data collection statisticsdata quality indicatorsdiffraction data analysisdiffraction data presentationmerging statisticsreciprocal space

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Area of Science:

  • Crystallography
  • Structural Biology
  • Data Science

Background:

  • The standard "Table 1" in biomolecular crystal structure reports summarizes data collection and processing statistics.
  • Current "Table 1" formats are insufficient for evaluating or replicating experiments.
  • Information in "Table 1" is often redundant with deposited diffraction data and contains debated metrics.

Purpose of the Study:

  • To advocate for the replacement of the traditional "Table 1" in scientific publications.
  • To propose a more effective method for presenting crystallographic data quality.
  • To improve the reproducibility and evaluation of biomolecular crystal structure experiments.

Main Methods:

  • Critically evaluate the current content and utility of "Table 1" in biomolecular crystallography.
  • Identify the limitations of existing data-collection and processing statistics.
  • Propose a new framework for data quality assessment.

Main Results:

  • "Table 1" is largely obsolete and inadequate for its intended purpose.
  • Existing metrics in "Table 1" lack clarity and are subject to scrutiny.
  • Deposited diffraction data contains more comprehensive information.

Conclusions:

  • The current "Table 1" format should be retired from biomolecular crystal structure publications.
  • A new system emphasizing direct data quality metrics from unmerged intensity data is recommended.
  • Graphical presentation of reciprocal space features and their impact on maps and models should be incorporated.